Wheat rusts never sleep but neither do sequencers: will pathogenomics transform the way plant diseases are managed?

Yellow rust, caused by Puccinia striiformis f. sp. tritici (PST), is a major disease of wheat and, together with stem rust (Puccinia graminis) and leaf rust (Puccinia triticina), causes some of the most devastating epidemics on wheat worldwide 1]. Control of these rust pathogens relies predominantly on breeding and deployment
of resistant varieties of wheat. To date, nearly 200 wheat-rust-resistance genes have
been catalogued 2]; however, resistance has often proved to be ephemeral owing to changes in the pathogen
population. In order to increase the durability of resistance, gene-deployment strategies
need to consider extant and potential pathogen variability. Although these concepts
are not new 3], their implementation was difficult until the advent of high-throughput sequencing
(HTS) and genotyping technologies.

Next-generation sequencing technologies provide new opportunities to study pathogens
and the hosts they infect. The increasing availability of crop and pathogen genomes
4] is providing new insights into pathogen biology, population structure and pathogenesis.
This provides new opportunities for disease management. An important input into resistance
breeding programs should be surveillance of the pathogen population. High-throughput
pathogenomics offers the possibility for analyzing a large number of pathogen isolates
and host varieties rapidly and at low cost.

In an article published in Genome Biology, Hubbard and colleagues 5] implemented a robust and rapid method to screen field isolates of PST and their host
cultivars. In this particular version of pathogenomics, a selected set of 39 samples
of infected wheat and triticale leaf tissue were collected directly from the field
in 2013 and analyzed using RNAseq. In addition, the genomes of 21 archived PST isolates
from the UK and France were also sequenced. Transcriptome analysis restricted the
amount of sequence necessary to obtain diagnostic information for both host and pathogen;
this not only accelerated genetic analysis of PST populations in situ but also allowed simultaneous assessment of the host genotype in the same sequencing
runs. Another advantage of transcriptome analysis is that it detects genes being expressed
and therefore the determinants of the interaction; thus, non-expressed genes present
in the genome do not obscure genotype-phenotype correlations.

From their analysis of over two million single-nucleotide polymorphisms (SNPs), Hubbard
and colleagues discovered that the shift in the 2013 PST population in the UK was
due to multiple exotic incursions, which resulted in the dominance of a diverse set
of new lineages 5]. The approach was dependent on the availability of draft reference genome assemblies,
which enabled the rapid assessment and characterization of variability in the pathogen
and host at high resolution 5]. However, a potential limitation of the method is that it only samples at one time-point
and does not reveal the genetic potential of non-expressed pathogen genes. Additionally,
the authors were able to correlate phenotypic and genotypic data; furthermore, the
sequencing data provided greater resolution than phenotyping on resistant cultivars
and revealed that some isolates with similar virulence phenotypes were genetically
distinct.